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gemma-4-E2B-it · Q8_0
NVIDIA RTX 507012GBllama.cpp b4200L0 Self-reported
This page aggregates 1 real-world runs of gemma-4-E2B-it (Q8_0) on NVIDIA RTX 5070 with llama.cpp, contributed by 1 independent source platforms; metrics are averages of published measurements.
— tok/s
Decode
Decode speed
— tok/s
Prefill
Prefill speed
— s
TTFT
Time to first token
— GB
VRAM
VRAM usage
L0 Self-reported
1
Measured runs
1
Independent sources
Other
Source platforms
Today
Last verified
Performance
No published records for this metric under the same model + hardware yet
Core figures
- Decode (avg)
- — tok/s
- Prefill (avg)
- — tok/s
- TTFT (avg)
- — s
- VRAM (avg)
- — GB
- MTP acceptance rate
- —
- TTFB
- — GB
- Power draw
- — W
Configuration
Member-level fields are taken from the most recent run
- Model
- gemma-4-E2B-it
- Quantization
- Q8_0
- Framework
- llama.cpp
- Version
- b4200
- Context length
- 4096 tokens
- Batch size
- 512
- GPU layers
- 99
- Flash Attention
- On
Hardware
Nominal and measured figures are shown side by side; whether it runs is the reader's call
- GPU
- NVIDIA RTX 5070
- Nominal VRAM
- 12 GB
- OS
- Linux
- Driver
- 570.65
- CUDA
- 12.6
Sources & evidence
1 measured records in total, each traceable to its original source
b4200 · Linux · CUDA 12.6 · 4096 ctx
— tok/s
Decode
— tok/s
Prefill
— s
TTFT
0 GB
VRAM
—
MTP
— W
Power draw
L0 理论估算：基于显存带宽 ÷ 模型体积公式，结合框架实测效率因子校准